The Mathematical Basis of the Expanding Relationship Scam Crime

The rapid global expansion of relationship scams is often described in social, psychological, or technological terms, but it can also be understood through a mathematical and evolutionary lens. When viewed this way, relationship scam crime behaves less like a series of isolated offenses and more like an adaptive system that responds dynamically to environmental pressures, human behavior, and information flow. Understanding this system helps explain why relationship scams continue to grow despite increased awareness, media coverage, and law enforcement attention.

Rooted in Darwin’s theory of natural selection, evolutionary explanations of antisocial and criminal behavior propose that certain exploitative strategies persist because they historically conferred survival or reproductive advantages. Across criminology, psychology, and evolutionary biology, scholars have explored how deception, cheating, dominance, and manipulation can function as adaptive strategies under certain conditions. Theories such as cheater theory, r/K selection theory, conditional adaptation theory, alternative adaptation theory, the staying alive hypothesis, and evolutionary neuroandrogenic theory all point to the same underlying idea. Antisocial behavior can emerge and persist when the perceived benefits outweigh the costs and when countermeasures are weak or inconsistent.

Relationship scams represent a modern digital manifestation of these ancient strategies. Rather than physical coercion or direct theft, offenders exploit emotional bonding, trust, attachment needs, and social norms. Digital platforms dramatically reduce risk to offenders while increasing access to a vast pool of potential targets. This asymmetry creates ideal conditions for evolutionary expansion.

The mathematical foundation of this process can be expressed through a standard evolution equation:

u′ = f(t, u)

In mathematical terms, this equation describes how a system changes over time based on its current state and influencing variables. In evolutionary biology, u represents the population or trait under consideration, t represents time, and f describes the forces acting on the system.

When applied to online relationship scam crime, the variables can be reframed in criminological terms. In this context:

• u represents the scale and sophistication of relationship scam crime
• t represents the population of potential victims
• f represents offender behavior, including adaptation, learning, and strategy development

Under this framing, the growth rate of scam crime depends on the interaction between offender strategies and victim availability. As long as there is a large and relatively unprotected pool of potential victims, offender behavior continues to evolve in ways that increase efficiency, believability, and reach. The equation’s feedback structure means that growth is not linear. Each successful scam produces resources, data, scripts, and psychological insights that are reinvested into future operations.

The key feature of this equation is feedback. The system feeds on its own outputs. Successful crime increases criminal capability, which in turn increases future success. This positive feedback loop explains why relationship scams do not merely persist but accelerate. New scripts are refined. Emotional manipulation becomes more precise. Technology is leveraged more effectively. Organized crime structures professionalize.

However, evolutionary systems do not expand indefinitely without resistance. The same equation implies that change occurs only when one of the variables is altered in a meaningful way. In biological systems, this often happens through environmental pressure or changes in survival strategies. In the context of relationship scams, the most influential pressure point is the victim population.

This leads to an expanded form of the equation:

u′ = f(t(−r), u)

Here, r represents recovery and information propagation among victims. This variable captures whether victims recover in a way that reduces future victimization or remain isolated, silent, or cognitively impaired in ways that unintentionally support continued offender success.

• When r is positive, victims recover, process the trauma, regain cognitive clarity, and share accurate information within their social networks. This reduces the effective victim pool. Scam tactics become less effective. Recruitment costs rise for offenders. Adaptation becomes harder and more resource-intensive.
• When r is negative, victims do not recover in a way that leads to meaningful information propagation. Shame, isolation, cognitive impairment, financial devastation, and social judgment silence them. In this case, the victim pool remains large or even grows, especially as previously victimized individuals become repeat targets. This condition accelerates expansion rather than slowing it.

This framing aligns closely with evolutionary theories of antisocial behavior. Cheater theory suggests that exploitative strategies thrive when detection and punishment are weak. Relationship scams fit this model well because detection is delayed, punishment is rare, and victims often blame themselves rather than offenders. Conditional adaptation theory suggests that individuals may adopt antisocial strategies when environmental conditions favor them. Digital anonymity, low enforcement risk, and global reach create precisely such conditions. Alternative adaptation theory and the staying alive hypothesis further support the idea that deception and manipulation can be selected for when they increase survival outcomes under constrained conditions.

The evolutionary neuroandrogenic theory adds another layer by linking risk-taking, dominance-seeking, and reduced empathy to biological mechanisms that can be amplified in criminal subcultures. When these traits are rewarded financially and socially within organized scam networks, selection pressure reinforces them further.

From this perspective, relationship scam crime is not simply a moral failure or technological problem. It is a dynamically adapting system responding rationally, in evolutionary terms, to its environment. Offenders adapt faster than institutions. Platforms prioritize growth over friction. Victims are fragmented, shamed, and under-supported. The result is a system that mathematically favors expansion.

The implication is critical. Suppression alone will never be sufficient. Law enforcement, platform moderation, and public awareness campaigns are necessary but incomplete. The most powerful variable in the equation is r, the rate and quality of victim recovery and information propagation. When victims are supported, educated, stabilized, and reintegrated into informed communities, the evolutionary environment changes. Scam strategies lose efficiency. Adaptation slows. Expansion curves flatten.

This approach does not place responsibility on victims. Instead, it recognizes that victim recovery is a systemic intervention point. Reducing shame, supporting cognitive recovery, and facilitating accurate information sharing are not just compassionate responses. They are mathematically and evolutionarily necessary countermeasures.

Incorporating evolutionary theory and mathematical modeling into mainstream criminological research offers a more complete understanding of relationship scam crime. It shifts the focus from isolated offenders to adaptive systems. It clarifies why the problem grows despite awareness. Most importantly, it identifies where meaningful change is possible.

Continued interdisciplinary research is needed to refine these models, validate assumptions, and integrate psychological recovery metrics into predictive frameworks. Assistance and collaboration across criminology, psychology, mathematics, and victim advocacy are essential for advancing this work and developing effective long-term strategies to counter relationship scam crime.

Prof. Tim McGuinness, Ph.D.
January 2026